Abstract 3267: Human population based engineered breast tumor model for in vivo biomarker discovery

Abstract

Abstract Human breast cancer development is a complex pathobiological process driven by genetic changes in normal epithelial cells which lead to uncontrollable growth in a permissive microenvironment. Therefore, it is not surprising that tumors from different patients exhibit variable responses to standard of care therapy with unfortunately only a small percentage of patients benefitting from therapy. It has therefore become a priority in oncology and personalized medicine to match patients to drugs that will result in a favorable treatment outcome. In this report, we describe a population based approach for response prediction featuring naturally occurring variation in tumors derived from genetically defined human-in-mouse models of cancer. De novo human breast tumors were generated by genetically engineering normal primary human breast epithelial cells with HER2 and SV40 early region (HER2/SV40er) or KRAS and SV40 early region (KRAS/SV40er) in an in vivo Human_In_Mouse (HIM) tissue transgenic model. The HER2/SV40er and the KRAS/SV40er HIM tumors develop as human breast adenocarcinoma that are histologically similar to those observed in patients. Also similar to that observed in human tumors, microarray profiling demonstrated significant inter-tumor variation among the established tumors. Moreover, the KRAS/SV40er tumors could be clustered with basal type breast cancers from patients, a poor prognosis human breast cancer subtype. Both HER2/SV40er and KRAS/SV40er tumors exhibited variable responses to treatments with the potent selective triple VEGFR inhibitor, tivozanib. Further characterization of those tumors, both pre- and post- treatment, identified potential biomarkers for tumor response to tivozanib. This population-based approach enables us to identify and validate biomarkers of therapeutic response in an in vivo human tumor model. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3267.